Optimization of energy consumption and surface roughness in slot milling of AISI 6061 T6 using the response surface method

Camposeco-Negrete, Carmita; Calderón-Nájera, Juan de Dios

doi:10.1007/s00170-019-03848-2

Cited by 24 publications

(6 citation statements)

References 21 publications

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“…The RSM method is a statistical method that is widely used to develop, improve, and optimize processes, where the response is in uenced by several variables. Furthermore, RSM uses statistical and mathematical techniques to shorten the time and number of tries in an experiment [13]. Therefore, RSM is widely used in several experiments related to machining processes, such as milling.…”

Section: Experimental Design Of Machining Parametersmentioning

confidence: 99%

“…Liu et al (2021) [12] developed a mathematical surface roughness model by applying the RSM technique during the bamboo milling process. Mathematical model with RSM technique is also used to optimize machining parameters on AISI 6061 T6 slot milling for surface roughness and energy consumption [13]. Davoodi and Eskandar (2015) [14] analyze tool wear and material removal of the iron nickel-based superalloy by optimizing the turning parameters and developing an empirical model based on RSM.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimisation of the Cutting Process on Machining Time of Ankle Foot as Transtibial Prosthesis Components Using Response Surface Methodology

Lestari

Adyono

Faizin

et al. 2023

Preprint

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Section: Experimental Design Of Machining Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimisation of the Cutting Process on Machining Time of Ankle Foot as Transtibial Prosthesis Components Using Response Surface Methodology

Lestari

Adyono

Faizin

et al. 2023

Preprint

View full text Add to dashboard Cite

“…Aluminium has wide utilization in the manufacturing industry due to its good mechanical and corrosive resistance properties. Further, aluminium has good sustainable assessment due to its abundant availability, ease of reuse, and recycling with less adverse environmental impacts [42,43]. Sandvik carbide inserts of different nose radius of ISO designation: CNMG 120404, CNMG 120408 and CNMG 120412 were selected as cutting tools with tool holder PCLNR 2020 K 12.…”

Section: Experimental Planningmentioning

confidence: 99%

Development of an Empirical Model for Variable Power Consumption Machining Processes: A Case of End Facing

2021

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Machining processes contribute significantly to the energy consumption of manufacturing industries, and reducing their energy consumption is a major challenge to achieve sustainable and cleaner manufacturing. The accurate and practical energy consumption prediction models for a machine tool are the foundation for sustainable and cleaner manufacturing. The machining of a workpiece mainly involves constant-power consumption machining processes e.g. turning and variablepower consumption machining processes e.g. end facing. The cutting power characteristics of the variable-power consumption machining processes are more complex and dynamic, due to change in one of the process parameters (e.g. cutting speed during end facing) than the constant-power consumption machining processes, and have received limited attention in the literature. In the present work, an empirical model is developed to predict the cutting energy consumption of the variable-power consumption machining process i.e. end facing. The end facing experiments were performed on a Computer Numerical Control Lathe in the dry and wet environment to obtain the fitting constants of the developed model. Four validation experiments were performed to confirm the prediction capability of the developed model. The validation experiments confirm that the accuracy of the developed model is more than 96%. Further, the predicted power profiles were in good agreement with the measured power profiles, which shows that the developed model satisfactorily encompasses the influences of the process parameters on the cutting power consumption.

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“…Finally, their findings showed that the cutting-edge stability of tested inserts influences tool life, cutting force stability, and the development of compressive residual stresses on the surface of the turned workpiece. Moreover, Camposeco-Negrete and de Dios Calderón-Ná jera [20] used multi-objective optimization to increase the productivity, energy efficiency, and surface quality of turning AISI 6061 T6 aluminum. Power consumption and surface roughness were optimized simultaneously by Sangwan and Kant [21].…”

Section: Introductionmentioning

confidence: 99%

Modelling the Effects of Workpiece Flexibility on Cutting Performance in Turning Operations

Ezugwu,

Fayomi,

Onifade

et al. 2023

JESA

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Machining is fundamentally a process of material removal. Therefore, machining productivity can be conceptualized as the rapid elimination of a substantial machining allowance, implying a reduction in machining time. This research has yielded a computational model predicated on beam deflection, factoring in the influence of workpiece flexibility on cutting forces, and its repercussions on the material removal rate and precision. The model facilitates the calculation of actual turning productivity. The methodology incorporated modeling the static response of the flexible workpiece to the thrust component of cutting forces. The impacts of flexibility on the beam model responses concerning the material removal rate, and deviations from the desired shape and size were scrutinized. A computational approach, experimentally corroborated, was applied. This approach necessitates cutting force coefficients, which were ascertained through cutting tests and pseudo-inverse regression analysis. The experimental setup for the cutting test incorporated a locally constructed dynamometer for measuring cutting forces, displays on both an LCD and a computer monitor for recording cutting force readings, a cutting tool, and a workpiece. Judging by the coefficients of determination, R 2 values of 0.97, 0.89, and 0.93 of the regression calibrating the force coefficients for the tangential, feed, and radial directions-which are used to gauge the accuracy of the determined force coefficient and are typically one or close to one-the derived force coefficients demonstrate high reliability. The developed model is projected to yield significant industrial-economic benefits by curtailing the costs of finishing operations on the CNC lathe machine, owing to the provision of a chronological path to follow while working on a flexible workpiece.

show abstract

Optimization of energy consumption and surface roughness in slot milling of AISI 6061 T6 using the response surface method

Cited by 24 publications

References 21 publications

Optimisation of the Cutting Process on Machining Time of Ankle Foot as Transtibial Prosthesis Components Using Response Surface Methodology

Optimisation of the Cutting Process on Machining Time of Ankle Foot as Transtibial Prosthesis Components Using Response Surface Methodology

Development of an Empirical Model for Variable Power Consumption Machining Processes: A Case of End Facing

Modelling the Effects of Workpiece Flexibility on Cutting Performance in Turning Operations

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